McArdle Laboratory for Cancer Research (Department of Oncology), Institute for Molecular Virology, and Carbone Cancer Center, University of Wisconsin-Madison, Madison, WI 53706, USA.
Laboratory for Optical and Computational Instrumentation, Center for Quantitative Cell Imaging, University of Wisconsin-Madison, Madison, WI 53706, USA.
Viruses. 2022 Apr 26;14(5):903. doi: 10.3390/v14050903.
Single-cell imaging has emerged as a powerful means to study viral replication dynamics and identify sites of virus−host interactions. Multivariate aspects of viral replication cycles yield challenges inherent to handling large, complex imaging datasets. Herein, we describe the design and implementation of an automated, imaging-based strategy, “Human Immunodeficiency Virus Red-Green-Blue” (HIV RGB), for deriving comprehensive single-cell measurements of HIV-1 unspliced (US) RNA nuclear export, translation, and bulk changes to viral RNA and protein (HIV-1 Rev and Gag) subcellular distribution over time. Differentially tagged fluorescent viral RNA and protein species are recorded using multicolor long-term (>24 h) time-lapse video microscopy, followed by image processing using a new open-source computational imaging workflow dubbed “Nuclear Ring Segmentation Analysis and Tracking” (NR-SAT) based on ImageJ plugins that have been integrated into the Konstanz Information Miner (KNIME) analytics platform. We describe a typical HIV RGB experimental setup, detail the image acquisition and NR-SAT workflow accompanied by a step-by-step tutorial, and demonstrate a use case wherein we test the effects of perturbing subcellular localization of the Rev protein, which is essential for viral US RNA nuclear export, on the kinetics of HIV-1 late-stage gene regulation. Collectively, HIV RGB represents a powerful platform for single-cell studies of HIV-1 post-transcriptional RNA regulation. Moreover, we discuss how similar NR-SAT-based design principles and open-source tools might be readily adapted to study a broad range of dynamic viral or cellular processes.
单细胞成像已成为研究病毒复制动态和鉴定病毒-宿主相互作用部位的有力手段。病毒复制周期的多变量方面对处理大型、复杂的成像数据集带来了固有挑战。在此，我们描述了一种自动化的基于成像的策略——“人类免疫缺陷病毒红绿蓝”（HIV RGB）的设计和实现，用于对 HIV-1 未剪接（US）RNA 核输出、翻译以及病毒 RNA 和蛋白质（HIV-1 Rev 和 Gag）亚细胞分布的整体变化进行全面的单细胞测量。使用多色长时（>24 h）延时视频显微镜记录差异标记的荧光病毒 RNA 和蛋白质种类，然后使用基于 ImageJ 插件的新开源计算成像工作流程“核环分割分析和跟踪”（NR-SAT）进行图像处理，该工作流程已集成到 Konstanz Information Miner（KNIME）分析平台中。我们描述了一个典型的 HIV RGB 实验设置，详细介绍了图像采集和 NR-SAT 工作流程，并附有分步教程，还展示了一个应用案例，其中我们测试了扰乱 Rev 蛋白亚细胞定位对 HIV-1 晚期基因调控动力学的影响，Rev 蛋白对 HIV-1 US RNA 的核输出至关重要。总之，HIV RGB 是研究 HIV-1 转录后 RNA 调控的单细胞研究的强大平台。此外，我们还讨论了如何轻松采用基于类似 NR-SAT 的设计原则和开源工具来研究广泛的动态病毒或细胞过程。
